An Investigation of the Nature and Extent of Human‐Robot Collaboration in Australian Industries

Human-Robot Collaboration (HRC) is an emerging field of research. Human-Robot Collaborations pose challenges for Human-Robot Interaction from a Human Factors (HF) perspective, many of which are only now being identified. Robot hardware capabilities and the sophistication of the algorithm protocols can impact the safety and efficiency of the robot interacting with the human.A narrative literature review identified limited evidence regarding the human capabilities, knowledge, and skills within human-robot collaboration both internationally and in Australia.This four (4) stage Master of Philosophy project investigated this relationship concerning the Human Factors elements of Human-Robot Collaboration.Stage 1 (Study 1) investigated the nature and extent of use of collaborative robots (cobots) in industry in Australia, using a mixed methods approach with an anonymous online survey (administered via Qualtrics) (n=5) and virtual face to face interviews with robotics academics, experts/ researchers, manufacturers & industry representatives (n=5). The study findings included: cobot users were principally large multinational companies; tasks mainly ‘pick and place’ and welding applications; main industries where cobots are used were food and packaging industries, and fabrication sector.Stage 2 (Study 2) investigated operators experiences with human-robot collaboration in industries in Australia. An exploratory mixed methods approach involved two parts: (Part A) a survey (n=3) and (Part B) a Focus Group discussion (n=3) with cobot operators. The study identified advantages of cobots included performance of tasks inherently difficult, monotonous or repetitive. Efficiencies of cobots included precision, reliability and repeatability. Stage 3 (Study 3) evaluated operators’ performance with a collaborative robot (cobot). This study utilised an observational methodology with experienced (n=3) and novice (n=8) operators. Operators performed ‘pick and place’ tasks with a cobot. Findings suggested experienced operators were more inclined to problem solve faults using a top-down problem-solving approach primarily interacting with the control tablet software program interface, whilst novices used operational bottom-up problem-solving methods such as trouble shooting using the ‘Stop’ ‘Reset Start’ control buttons to rectify a forced stop. Both experienced and novice operators were efficient in their problem-solving strategies.Informed by the findings of Stages 1, 2 and 3, Stage 4 provided recommendations for improving training strategies for operators who work with collaborative robots (cobots) in industry that could potentially increase the efficiency of the human contribution in collaborative tasks performed with a cobot.